DiceDesign and DiceEval: Two R Packages for Design and Analysis of Computer Experiments

Autor: Delphine Dupuy, Céline Helbert, Jessica Franco

Publikováno v: Journal of Statistical Software, Vol 65, Iss 1, Pp 1-38 (2015)

This paper introduces two R packages available on the Comprehensive R Archive network. The main application concerns the study of computer code output. Package DiceDesign is dedicated to numerical design of experiments, from the construction to the s

Externí odkaz: https://doaj.org/article/edfdb374d54a4317980b16627ff794e4

Metamodeling approaches to help designing vegetative filter strips and improve the water quality

Autor: Claire Lauvernet, Céline Helbert, Zhu Xujia, Bruno Sudret

Publikováno v: EGUsphere

Significant amounts of pollutant are measured in surface water, their presence due in part to the use of pesticides in agriculture. One solution to limit pesticide transfer by surface runoff is to implement vegetative filter strips (VFS) along rivers

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4b4ff8603d056046abdc59fb2126266
https://doi.org/10.5194/egusphere-egu22-10539

Four algorithms to construct a sparse kriging kernel for dimensionality reduction

Autor: Christophette Blanchet-Scalliet, Mélina Ribaud, Céline Helbert, Céline Vial

Publikováno v: Computational Statistics. 34:1889-1909

In the context of computer experiments, metamodels are largely used to represent the output of computer codes. Among these models, Gaussian process regression (kriging) is very efficient see e.g Snelson (Flexible and efficient Gaussian process models

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::4537fac3212ac847890b26517df46496
https://doi.org/10.1007/s00180-019-00874-2

Data-driven Stochastic Inversion via Functional Quantization

Autor: Céline Helbert, Clémentine Prieur, Olivier Lepreux, Miguel Munoz Zuniga, Delphine Sinoquet, Mohamed Reda El Amri

Publikováno v: Statistics and Computing
Statistics and Computing, Springer Verlag (Germany), 2020, 30 (3), pp.525-541. ⟨10.1007/s11222-019-09888-8⟩
Statistics and Computing, 2020, 30 (3), pp.525-541. ⟨10.1007/s11222-019-09888-8⟩

International audience; In this paper, we propose a new methodology for solving stochastic inversion problems through computer experiments, the stochasticity being driven by a functional random variables. This study is motivated by an automotive appl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2703e9a14ff08a548441680c6adf1973
https://hal.inria.fr/hal-01704189v3/document

Robust optimization: a kriging-based multi-objective optimization approach

Autor: Mélina Ribaud, Frederic Gillot, Céline Helbert, Christophette Blanchet-Scalliet

Publikováno v: Reliability Engineering and System Safety
Reliability Engineering and System Safety, Elsevier, 2020, 200, pp.30. ⟨10.1016/j.ress.2020.106913⟩
Reliability Engineering and System Safety, 2020, 200, pp.30. ⟨10.1016/j.ress.2020.106913⟩

In the robust shape optimization context, the evaluation cost of numerical models is reduced by the use of a response surface. Multi-objective methodologies for robust optimization that consist in simultaneously minimizing the expectation and varianc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b20c184b1c58a7e1b01047e3ea04a9d7
https://hal.archives-ouvertes.fr/hal-01829889